Real-time prediction and correction of scheduled service bunching

ABSTRACT

A method includes: a computer receiving historical data from at least one service vehicle; the computer receiving network definitions for the least one service vehicle; the computer receiving dynamic data from the at least one service vehicle; and the computer developing predictions and corrective actions to prevent service bunching, based upon the historical data, the network definitions, and the dynamic data.

BACKGROUND

The present invention relates to real-time prediction and correction, and more specifically, to provide corrective actions for scheduled service vehicles to prevent bunching.

SUMMARY

According to one aspect of the present invention, a method includes: a computer receiving historical data from at least one service vehicle; the computer receiving network definitions for the least one service vehicle; the computer receiving dynamic data from the at least one service vehicle; and the computer developing predictions and corrective actions to prevent service bunching based upon the historical data, the network definitions, and the dynamic data.

According to another aspect of the present invention, a computer system includes: one or more processors, one or more computer-readable memories and one or more computer-readable, tangible storage devices; a historical database operatively coupled to at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, configured to receive static data from at least one service vehicle; a network definition database operatively coupled to at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, configured to receive network definitions for the least one service vehicle; a communication unit operatively coupled to at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, configured to receive dynamic data from the at least one service vehicle; and a prediction unit operatively coupled to at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, configured to develop predictions and corrective actions to prevent service bunching based upon the historical data, the network definitions, and the dynamic data.

According to still another aspect of the present invention, a computer program product includes: one or more computer-readable, tangible storage medium; program instructions, stored on at least one of the one or more storage medium, to receive historical data from at least one service vehicle; program instructions, stored on at least one of the one or more storage medium, to receive network definitions for the least one service vehicle; program instructions, stored on at least one of the one or more storage medium, to receive dynamic data from the at least one service vehicle; and program instructions, stored on at least one of the one or more storage medium, to develop predictions and corrective actions to prevent service bunching based upon the historical data, the network definitions, and the dynamic data.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 shows a flowchart according to an embodiment of the present invention.

FIG. 2 shows an exemplary implementation according to an embodiment of the present invention.

FIG. 3 illustrates a hardware configuration according to an embodiment of the present invention.

DETAILED DESCRIPTION

Before explaining at least one embodiment of the invention in detail, it is to be understood that the invention is not limited in its application to the details of construction and the arrangement of the components set forth in the following description or illustrated in the drawings. The invention is applicable to other embodiments or of being practiced or carried out in various ways. Also, it is to be understood that the phraseology and terminology employed herein is for the purpose of description and should not be regarded as limiting. As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or computer program product.

Referring to FIG. 1, to prevent service vehicle bunching a process includes gathering static historical data (102) from a service provider. The historical data includes digital traces such as congestion patterns, vehicle performances and breakdowns, sequence of service vehicles positions versus time. The process further uses network definition of service routes (105) set by a service provider. While the routes and service stops may very over years, the routes are fairly consistent. The process further uses passenger models (107) for the service routes. The passenger models specifically address capturing dwell times at the service stops. Another way to capture passenger model data is to use an automatic passenger counting device on the service vehicle itself. Still another way to capture passenger model data is via the use of metro cards at the entry points for the service vehicles. Another process aspect of the invention is to receive dynamic real time fleet traces for the service vehicles (109). The data from the dynamic real time, static data, network definitions and passenger models is supplied to a prediction component unit (112). The output of the prediction unit includes route predictions, computing accuracy measurements, short term forecasting of when bunching is likely to occur, passenger loads, time trajectories for the service vehicles along a route, time trajectories of the service vehicles over different days. Once the various predictions are generated they are supplied to an optimization component (115). The optimization issues alerts and recommends control strategies to the operator of the service vehicle (118) or a network infrastructure. Some of the alerts and recommendations to prevent service bunching of service vehicles may include to slow the vehicle down, skip a stop, speed up, hold position, adjust dispatch at the start terminal or modify the schedule so that a service vehicle does not bunch up with other service vehicles. The alerts can still further include supplying transit information to the passengers or controlling the traffic signaling system.

Referring to FIG. 2, an exemplary implementation according to an embodiment of the present invention shows a service vehicle network. The service network controller 203 uses a historical database 204, a network definition database 206 and a passenger model database 205 and feeds the data these databases to a prediction unit 208. The service network controller 203 further uses the communication device 207, via it's antenna 210, to receive real time data from the service vehicles (220, 222, 224, 226 and 228) via their respective antennas (221, 223, 225, 227, and 229). The real time data is also supplied to the prediction unit 208. The prediction unit 208 then issues service network bunching predictions pertaining to the service vehicles (220, 222, 224, 226 and 228). The predictions are feed to an optimization unit 209. The optimization unit 209 takes the highest predictions and issues service actions to the service vehicles (220, 222, 224, 226 and 228) using the communication device 207. The service vehicles (buses and trains) operate on roads and/or train railways such that some of the alerts and recommendations may include to slow the vehicle down, skip a road bus stop (train rail stop), speed up, hold position, adjust dispatch at the start terminal or modify the bus or train schedule.

Referring to FIG. 2, an exemplary implementation according to an embodiment of the present invention shows a service vehicle network. The service network controller 203 uses a historical database 204, a network definition database 206 and a passenger model database 205 and feeds the data these databases to a prediction unit 208. The service network controller 203 further uses the communication device 207, via it's antenna 210, to receive real time data from the service vehicles (220, 222, 224, 226 and 228) via their respective antennas (221, 223, 225, 227, and 229). The real time data is also supplied to the prediction unit 208. The prediction unit 208 then issues service network bunching predictions pertaining to the service vehicles (220, 222, 224, 226 and 228). The predictions are feed to an optimization unit 209. The optimization unit 209 takes the highest predictions and issues service actions to the service vehicles (220, 222, 224, 226 and 228) using the communication device 207. The service vehicles (buses and trains) operate on roads and/or train railways such that some of the alerts and recommendations may include to slow the vehicle down, skip a road bus stop (train rail stop), speed up, hold position, adjust dispatch at the start terminal or modify the bus or train schedule.

Any combination of one or more computer readable medium(s) may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc. or any suitable combination of the foregoing.

Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).

Aspects of the present invention are described below with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

Referring now to FIG. 3, this schematic drawing illustrates a hardware configuration of an information handling/computer system in accordance with the embodiments of the invention. The system comprises at least one processor or central processing unit (CPU) 310. The CPUs 310 are interconnected via system bus 312 to various devices such as a random access memory (RAM) 314, read-only memory (ROM) 316, and an input/output (I/O) adapter 318. The I/O adapter 318 can connect to peripheral devices, such as disk units 311 and tape drives 313, or other program storage devices that are readable by the system. The system can read the inventive instructions on the program storage devices and follow these instructions to execute the methodology of the embodiments of the invention. The system further includes a user interface adapter 319 that connects a keyboard 315, mouse 317, speaker 324, microphone 322, and/or other user interface devices such as a touch screen device (not shown) to the bus 312 to gather user input. Additionally, a communication adapter 320 connects the bus 312 to a data processing network 325, and a display adapter 321 connects the bus 312 to a display device 323 which may be embodied as an output device such as a monitor, printer, or transmitter, for example.

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of all means or step plus function elements in the claims below are intended to include any structure, material, or act for performing the function in combination with other claimed elements as specifically claimed. The description of the present invention has been presented for purposes of illustration and description, but is not intended to be exhaustive or limited to the invention in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the invention. The embodiment was chosen and described in order to best explain the principles of the invention and the practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated. 

What is claimed is:
 1. A computer system comprising: one or more processors, one or more computer-readable memories and one or more computer-readable, tangible storage devices; a service network controller operatively coupled to at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, is configured to receive historical data from at least one service bus vehicle from a fleet of service bus vehicles; the service network controller operatively coupled to at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, is further configured to receive network definitions of service routes for the least one service bus vehicle from the fleet of service bus vehicles; the service network controller operatively coupled to at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, is further configured to receive dynamic data from the at least one service bus vehicle from the fleet of service bus vehicles; the service network controller operatively coupled to at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, is further configured to receive passenger model data when the passenger uses a card upon boarding the least one service bus vehicle from the fleet of service bus vehicles; and the service network controller operatively coupled to at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, is further configured to develop route predictions and corrective actions to prevent service bunching for the fleet of service bus vehicles, based upon the historical data, the network route definitions, and the dynamic data, wherein the service bus vehicles operate on roads such that one of the corrective actions may include to skip a road bus stop.
 2. The system according to claim 1, wherein the route predictions are used to prevent service bunching for the at least one service bus vehicle amongst the fleet of service bus vehicles.
 3. The system according to claim 1, wherein another one of the corrective actions include optimizing route plans to prevent predicted service bunching amongst the fleet of service bus vehicles along a network of scheduled services.
 4. The system according to claim 3, historical data includes past performance of at least one service bus vehicle from the fleet of service bus vehicles.
 5. The system according to claim 3, wherein the dynamic data is real time data from the at least one service bus vehicle from the fleet of service bus vehicles.
 6. The system according to claim 3, wherein the service network controller sends the optimized route plans to a network infrastructure to prevent the service bunching.
 7. A computer program product comprising: one or more computer-readable, tangible storage medium; program instructions, stored on at least one of the one or more storage medium, to cause a service network controller to receive historical data from at least one service bus vehicle from a fleet of service bus vehicles; program instructions, stored on at least one of the one or more storage medium, to cause the service network controller to receive network definitions of service routes for the least one service bus vehicle from the fleet of service bus vehicles; program instructions, stored on at least one of the one or more storage medium, to cause the service network controller to receive dynamic data from the at least one service bus vehicle from the fleet of service bus vehicles; program instructions, stored on at least one of the one or more storage medium, to cause the service network controller to receive passenger model data when the passenger uses a card upon boarding the least one service bus vehicle from the fleet of service bus vehicles; and program instructions, stored on at least one of the one or more storage medium, to cause the service network controller to develop route predictions and corrective actions to prevent service bunching for the fleet of service bus vehicles, based upon the historical data, the network route definitions, and the dynamic data, wherein the service bus vehicles operate on roads such that one of the corrective actions may include to skip a road bus stop.
 8. The computer program product according to claim 7, wherein another one of the corrective actions include optimizing route plans to prevent predicted service bunching for the fleet of service bus vehicles along a network of scheduled services.
 9. The computer program product according to claim 8, further comprising program instructions, stored on at least one of the one or more storage medium, to cause the service network controller to send the optimized route plans to a network infrastructure to prevent service bunching for the fleet of service bus vehicles. 